Changeset 5023
- Timestamp:
- 12/04/10 18:08:43 (14 years ago)
- Location:
- branches/HeuristicLab.MetaOptimization
- Files:
-
- 15 edited
Legend:
- Unmodified
- Added
- Removed
-
branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/HeuristicLab.MetaOptimization.Test.csproj
r4997 r5023 69 69 </Reference> 70 70 <Reference Include="HeuristicLab.Algorithms.GeneticAlgorithm-3.3"> 71 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Algorithms.GeneticAlgorithm-3.3.dll</HintPath>71 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Algorithms.GeneticAlgorithm-3.3.dll</HintPath> 72 72 </Reference> 73 73 <Reference Include="HeuristicLab.Algorithms.LocalSearch-3.3"> … … 96 96 </Reference> 97 97 <Reference Include="HeuristicLab.Collections-3.3"> 98 <HintPath>..\..\ HeuristicLab.Hive\sources\HeuristicLab.Hive\HeuristicLab.Hive.Slave.Core\3.3\bin\Debug\HeuristicLab.Collections-3.3.dll</HintPath>98 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Collections-3.3.dll</HintPath> 99 99 </Reference> 100 100 <Reference Include="HeuristicLab.Common-3.3"> 101 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Common-3.3.dll</HintPath>101 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Common-3.3.dll</HintPath> 102 102 </Reference> 103 103 <Reference Include="HeuristicLab.Common.Resources-3.3"> … … 105 105 </Reference> 106 106 <Reference Include="HeuristicLab.Core-3.3"> 107 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Core-3.3.dll</HintPath>107 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Core-3.3.dll</HintPath> 108 108 </Reference> 109 109 <Reference Include="HeuristicLab.Core.Views-3.3"> … … 111 111 </Reference> 112 112 <Reference Include="HeuristicLab.Data-3.3"> 113 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Data-3.3.dll</HintPath>113 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Data-3.3.dll</HintPath> 114 114 </Reference> 115 115 <Reference Include="HeuristicLab.Data.Views-3.3"> 116 116 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Data.Views-3.3.dll</HintPath> 117 117 </Reference> 118 <Reference Include="HeuristicLab.DebugEngine-3.3"> 119 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.DebugEngine-3.3.dll</HintPath> 120 </Reference> 118 121 <Reference Include="HeuristicLab.Encodings.BinaryVectorEncoding-3.3"> 119 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.BinaryVectorEncoding-3.3.dll</HintPath>120 </Reference> 121 <Reference Include="HeuristicLab.Encodings.IntegerVectorEncoding-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">122 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.IntegerVectorEncoding-3.3.dll</HintPath>122 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.BinaryVectorEncoding-3.3.dll</HintPath> 123 </Reference> 124 <Reference Include="HeuristicLab.Encodings.IntegerVectorEncoding-3.3"> 125 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.IntegerVectorEncoding-3.3.dll</HintPath> 123 126 </Reference> 124 127 <Reference Include="HeuristicLab.Encodings.PermutationEncoding-3.3"> 125 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.PermutationEncoding-3.3.dll</HintPath>128 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.PermutationEncoding-3.3.dll</HintPath> 126 129 </Reference> 127 130 <Reference Include="HeuristicLab.Encodings.PermutationEncoding.Views-3.3"> 128 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.PermutationEncoding.Views-3.3.dll</HintPath>129 </Reference> 130 <Reference Include="HeuristicLab.Encodings.RealVectorEncoding-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">131 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.RealVectorEncoding-3.3.dll</HintPath>131 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.PermutationEncoding.Views-3.3.dll</HintPath> 132 </Reference> 133 <Reference Include="HeuristicLab.Encodings.RealVectorEncoding-3.3"> 134 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.RealVectorEncoding-3.3.dll</HintPath> 132 135 </Reference> 133 136 <Reference Include="HeuristicLab.Encodings.SymbolicExpressionTreeEncoding-3.3"> … … 152 155 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Netron-3.0.2672.12446.dll</HintPath> 153 156 </Reference> 154 <Reference Include="HeuristicLab.Operators-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">155 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Operators-3.3.dll</HintPath>157 <Reference Include="HeuristicLab.Operators-3.3"> 158 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Operators-3.3.dll</HintPath> 156 159 </Reference> 157 160 <Reference Include="HeuristicLab.Operators.Programmable-3.3"> … … 164 167 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Operators.Views.GraphVisualization-3.3.dll</HintPath> 165 168 </Reference> 166 <Reference Include="HeuristicLab.Optimization-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">167 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Optimization-3.3.dll</HintPath>169 <Reference Include="HeuristicLab.Optimization-3.3"> 170 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Optimization-3.3.dll</HintPath> 168 171 </Reference> 169 172 <Reference Include="HeuristicLab.Optimization.Operators-3.3"> … … 174 177 </Reference> 175 178 <Reference Include="HeuristicLab.Optimizer-3.3"> 176 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Optimizer-3.3.dll</HintPath>177 </Reference> 178 <Reference Include="HeuristicLab.Parameters-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">179 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Parameters-3.3.dll</HintPath>179 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Optimizer-3.3.dll</HintPath> 180 </Reference> 181 <Reference Include="HeuristicLab.Parameters-3.3"> 182 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Parameters-3.3.dll</HintPath> 180 183 </Reference> 181 184 <Reference Include="HeuristicLab.Parameters.Views-3.3"> 182 185 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Parameters.Views-3.3.dll</HintPath> 183 186 </Reference> 184 <Reference Include="HeuristicLab.Persistence-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">185 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Persistence-3.3.dll</HintPath>187 <Reference Include="HeuristicLab.Persistence-3.3"> 188 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Persistence-3.3.dll</HintPath> 186 189 </Reference> 187 190 <Reference Include="HeuristicLab.Persistence.GUI-3.3"> 188 191 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Persistence.GUI-3.3.dll</HintPath> 189 192 </Reference> 190 <Reference Include="HeuristicLab.PluginInfrastructure-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">191 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.PluginInfrastructure-3.3.dll</HintPath>193 <Reference Include="HeuristicLab.PluginInfrastructure-3.3"> 194 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.PluginInfrastructure-3.3.dll</HintPath> 192 195 </Reference> 193 196 <Reference Include="HeuristicLab.Problems.ArtificialAnt-3.3"> … … 230 233 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Problems.Knapsack.Views-3.3.dll</HintPath> 231 234 </Reference> 235 <Reference Include="HeuristicLab.Problems.MetaOptimization-3.3"> 236 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Problems.MetaOptimization-3.3.dll</HintPath> 237 </Reference> 238 <Reference Include="HeuristicLab.Problems.MetaOptimization.Views-3.3"> 239 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Problems.MetaOptimization.Views-3.3.dll</HintPath> 240 </Reference> 232 241 <Reference Include="HeuristicLab.Problems.OneMax-3.3"> 233 242 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Problems.OneMax-3.3.dll</HintPath> … … 237 246 </Reference> 238 247 <Reference Include="HeuristicLab.Problems.TestFunctions-3.3"> 239 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Problems.TestFunctions-3.3.dll</HintPath>248 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Problems.TestFunctions-3.3.dll</HintPath> 240 249 </Reference> 241 250 <Reference Include="HeuristicLab.Problems.TestFunctions.Views-3.3"> … … 257 266 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.ProtobufCS-0.9.1.dll</HintPath> 258 267 </Reference> 259 <Reference Include="HeuristicLab.Random-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">260 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Random-3.3.dll</HintPath>261 </Reference> 262 <Reference Include="HeuristicLab.Selection-3.3 , Version=3.3.0.0, Culture=neutral, PublicKeyToken=ba48961d6f65dcec, processorArchitecture=MSIL">263 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Selection-3.3.dll</HintPath>268 <Reference Include="HeuristicLab.Random-3.3"> 269 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Random-3.3.dll</HintPath> 270 </Reference> 271 <Reference Include="HeuristicLab.Selection-3.3"> 272 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Selection-3.3.dll</HintPath> 264 273 </Reference> 265 274 <Reference Include="HeuristicLab.SequentialEngine-3.3"> 266 <HintPath>..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.SequentialEngine-3.3.dll</HintPath>275 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.SequentialEngine-3.3.dll</HintPath> 267 276 </Reference> 268 277 <Reference Include="HeuristicLab.SharpDevelop-3.1.1.5327"> … … 311 320 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\WeifenLuo.WinFormsUI.Docking-2.3.1.dll</HintPath> 312 321 </Reference> 322 <Reference Include="ZedGraph"> 323 <HintPath>..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\ZedGraph.dll</HintPath> 324 </Reference> 313 325 </ItemGroup> 314 326 <ItemGroup> 315 327 <Compile Include="Program.cs" /> 316 328 <Compile Include="Properties\AssemblyInfo.cs" /> 317 </ItemGroup>318 <ItemGroup>319 <ProjectReference Include="..\HeuristicLab.Problems.MetaOptimization\3.3\HeuristicLab.Problems.MetaOptimization-3.3.csproj">320 <Project>{ABBC1DF6-FCC6-4F86-AB75-B6B3A72E7D17}</Project>321 <Name>HeuristicLab.Problems.MetaOptimization-3.3</Name>322 </ProjectReference>323 329 </ItemGroup> 324 330 <ItemGroup> -
branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.Test/Program.cs
r5009 r5023 12 12 using HeuristicLab.Random; 13 13 using HeuristicLab.Optimization; 14 using HeuristicLab.Common; 15 using System.IO; 16 using HeuristicLab.Problems.TestFunctions; 17 using System.Text; 18 using HeuristicLab.Selection; 14 19 15 20 namespace HeuristicLab.MetaOptimization.Test { 16 21 class Program { 17 private static int metaAlgorithmPopulationSize = 20; 18 private static int metaAlgorithmMaxGenerations = 100; 19 20 private static int baseAlgorithmPopulationSize = 20; 21 private static int baseAlgorithmMaxGenerations = 30; 22 private static int metaAlgorithmPopulationSize = 40; 23 private static int metaAlgorithmMaxGenerations = 30; 24 25 private static int baseAlgorithmMaxGenerations = 100; 22 26 23 27 static void Main(string[] args) { … … 31 35 IValueConfiguration algorithmVc = SetupAlgorithm(baseLevelAlgorithm, metaOptimizationProblem); 32 36 33 Console.WriteLine("Press enter to start");34 Console.ReadLine();35 TestConfiguration(algorithmVc, baseLevelAlgorithm);36 37 Console.WriteLine("Press enter to start");38 Console.ReadLine();37 //Console.WriteLine("Press enter to start"); 38 //Console.ReadLine(); 39 //TestConfiguration(algorithmVc, baseLevelAlgorithm); 40 41 //Console.WriteLine("Press enter to start"); 42 //Console.ReadLine(); 39 43 TestOptimization(metaLevelAlgorithm); 40 44 … … 50 54 Console.ReadLine(); 51 55 56 var clones = new List<object>(); 52 57 for (int i = 0; i < 1000; i++) { 53 58 var clone = algorithmVc.Clone(); 59 clones.Add(clone); 54 60 } 55 61 … … 70 76 metaLevelAlgorithm.Problem = metaOptimizationProblem; 71 77 metaLevelAlgorithm.Engine = new SequentialEngine.SequentialEngine(); 78 79 metaLevelAlgorithm.Mutator = new ParameterConfigurationManipulator(); 80 metaLevelAlgorithm.MutationProbability.Value = 0.15; 81 72 82 return metaLevelAlgorithm; 73 83 } 74 84 75 85 private static IValueConfiguration SetupAlgorithm(GeneticAlgorithm baseLevelAlgorithm, MetaOptimizationProblem metaOptimizationProblem) { 76 baseLevelAlgorithm.Problem = new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() { ProblemSize = new IntValue(2000) }; 77 baseLevelAlgorithm.PopulationSize.Value = baseAlgorithmPopulationSize; 86 baseLevelAlgorithm.Problem = new HeuristicLab.Problems.TestFunctions.SingleObjectiveTestFunctionProblem() { 87 Evaluator = new GriewankEvaluator(), 88 ProblemSize = new IntValue(1000) 89 }; 78 90 baseLevelAlgorithm.MaximumGenerations.Value = baseAlgorithmMaxGenerations; 79 91 … … 85 97 ConfigureMutationRate(algorithmVc); 86 98 ConfigureMutationOperator(algorithmVc); 99 ConfigureElites(algorithmVc); 100 ConfigureSelectionOperator(algorithmVc); 87 101 return algorithmVc; 88 102 } 89 103 90 104 private static void TestConfiguration(IValueConfiguration algorithmVc, GeneticAlgorithm baseLevelAlgorithm) { 91 IRandom rand = new MersenneTwister();105 IRandom rand = new FastRandom(0); 92 106 // set random values 93 107 for (int i = 0; i < 10; i++) { … … 99 113 Console.WriteLine(string.Format("MutRate: original: {0}, randomized: {1}", baseLevelAlgorithm.MutationProbability, newAlg.MutationProbability)); 100 114 Console.WriteLine(string.Format("MutOp: original: {0}, randomized: {1}", baseLevelAlgorithm.Mutator, newAlg.Mutator)); 101 } 102 115 Console.WriteLine(string.Format("SelOp: original: {0}, randomized: {1}", baseLevelAlgorithm.Selector, newAlg.Selector)); 116 Console.WriteLine(string.Format("GrSi: original: {0}, randomized: {1}", "?", ((TournamentSelector)newAlg.Selector).GroupSizeParameter.Value)); 117 Console.WriteLine("---"); 118 } 119 120 Console.WriteLine("======================="); 121 algorithmVc.Randomize(rand); 122 algorithmVc.Parameterize(baseLevelAlgorithm); 103 123 // mutate 104 124 for (int i = 0; i < 10; i++) { … … 110 130 Console.WriteLine(string.Format("MutRate: original: {0}, mutated: {1}", baseLevelAlgorithm.MutationProbability, newAlg.MutationProbability)); 111 131 Console.WriteLine(string.Format("MutOp: original: {0}, mutated: {1}", baseLevelAlgorithm.Mutator, newAlg.Mutator)); 112 } 113 132 Console.WriteLine(string.Format("SelOp: original: {0}, mutated: {1}", baseLevelAlgorithm.Selector, newAlg.Selector)); 133 Console.WriteLine(string.Format("GrSi: original: {0}, mutated: {1}", ((TournamentSelector)baseLevelAlgorithm.Selector).GroupSizeParameter.Value, ((TournamentSelector)newAlg.Selector).GroupSizeParameter.Value)); 134 Console.WriteLine("---"); 135 } 136 137 Console.WriteLine("======================="); 114 138 // cross 115 139 for (int i = 0; i < 10; i++) { 116 140 IValueConfiguration clonedVc1 = (IValueConfiguration)algorithmVc.Clone(); 141 IValueConfiguration clonedVc2 = (IValueConfiguration)algorithmVc.Clone(); 142 143 GeneticAlgorithm first = (GeneticAlgorithm)clonedVc1.ActualValue.Value.Clone(); 144 GeneticAlgorithm second = (GeneticAlgorithm)clonedVc2.ActualValue.Value.Clone(); 145 117 146 clonedVc1.Randomize(rand); 118 clonedVc1.Parameterize(baseLevelAlgorithm); 119 120 IValueConfiguration clonedVc2 = (IValueConfiguration)algorithmVc.Clone(); 121 GeneticAlgorithm first = (GeneticAlgorithm)clonedVc1.ActualValue.Value; 122 GeneticAlgorithm second = (GeneticAlgorithm)clonedVc2.ActualValue.Value; 147 clonedVc1.Parameterize(first); 148 149 clonedVc2.Randomize(rand); 150 clonedVc2.Parameterize(second); 123 151 124 152 var popSizeBefore = first.PopulationSize.Value; 125 153 var mutRateBefore = first.MutationProbability.Value; 126 154 var mutOpBefore = first.Mutator; 155 var selOpBefore = first.Selector; 156 var groupSizeBefore = ((TournamentSelector)first.Selector).GroupSizeParameter.Value.Value; 127 157 128 158 clonedVc1.Cross(clonedVc2, rand); 129 clonedVc1.Parameterize( (GeneticAlgorithm)clonedVc2.ActualValue.Value);159 clonedVc1.Parameterize(first); 130 160 131 161 Console.WriteLine(string.Format("PopSize: first: {0}, second: {1}, crossed: {2}", popSizeBefore, second.PopulationSize, first.PopulationSize)); 132 162 Console.WriteLine(string.Format("MutRate: first: {0}, second: {1}, crossed: {2}", mutRateBefore, second.MutationProbability, first.MutationProbability)); 133 Console.WriteLine(string.Format("MutRate: first: {0}, second: {1}, crossed: {2}", mutOpBefore, second.Mutator, first.Mutator)); 134 } 163 Console.WriteLine(string.Format("MutOp: first: {0}, second: {1}, crossed: {2}", mutOpBefore, second.Mutator, first.Mutator)); 164 Console.WriteLine(string.Format("SelOp: first: {0}, second: {1}, crossed: {2}", selOpBefore, second.Selector, first.Selector)); 165 Console.WriteLine(string.Format("GrSi: first: {0}, second: {1}, crossed: {2}", groupSizeBefore, ((TournamentSelector)second.Selector).GroupSizeParameter.Value, ((TournamentSelector)first.Selector).GroupSizeParameter.Value)); 166 Console.WriteLine("---"); 167 } 168 Console.WriteLine("======================="); 135 169 } 136 170 … … 144 178 mutationOperator.ValueConfigurations.SetItemCheckedState(multiMutator, false); 145 179 } 180 } 181 182 private static void ConfigureSelectionOperator(IValueConfiguration algorithmVc) { 183 var selectionOperatorPc = algorithmVc.ParameterConfigurations.Where(x => x.Name == "Selector").SingleOrDefault(); 184 selectionOperatorPc.Optimize = true; 185 186 foreach (var vc in selectionOperatorPc.ValueConfigurations) { 187 if (vc.ActualValue.ValueDataType == typeof(TournamentSelector)) { 188 selectionOperatorPc.ValueConfigurations.SetItemCheckedState(vc, true); 189 vc.Optimize = true; 190 ConfigureTournamentGroupSize(vc); 191 } else { 192 selectionOperatorPc.ValueConfigurations.SetItemCheckedState(vc, false); 193 } 194 } 195 } 196 197 private static void ConfigureTournamentGroupSize(IValueConfiguration tournamentVc) { 198 var groupSizePc = tournamentVc.ParameterConfigurations.Where(x => x.ParameterName == "GroupSize").SingleOrDefault(); 199 groupSizePc.Optimize = true; 200 201 groupSizePc.ValueConfigurations.First().Optimize = true; 202 groupSizePc.ValueConfigurations.First().RangeConstraint.LowerBound = new IntValue(0); 203 groupSizePc.ValueConfigurations.First().RangeConstraint.UpperBound = new IntValue(100); 204 groupSizePc.ValueConfigurations.First().RangeConstraint.StepSize = new IntValue(1); 146 205 } 147 206 … … 151 210 var populationSizeVc = populationSizePc.ValueConfigurations.First(); 152 211 populationSizeVc.Optimize = true; 153 populationSizeVc.RangeConstraint.LowerBound = new IntValue( 0);212 populationSizeVc.RangeConstraint.LowerBound = new IntValue(20); 154 213 populationSizeVc.RangeConstraint.UpperBound = new IntValue(100); 155 214 populationSizeVc.RangeConstraint.StepSize = new IntValue(1); … … 166 225 } 167 226 227 private static void ConfigureElites(IValueConfiguration algorithmVc) { 228 var elitesPc = algorithmVc.ParameterConfigurations.Where(x => x.Name == "Elites").SingleOrDefault(); 229 elitesPc.Optimize = true; 230 var elitesVc = elitesPc.ValueConfigurations.First(); 231 elitesVc.Optimize = true; 232 elitesVc.RangeConstraint.LowerBound = new IntValue(0); 233 elitesVc.RangeConstraint.UpperBound = new IntValue(20); 234 elitesVc.RangeConstraint.StepSize = new IntValue(1); 235 } 236 168 237 private static void TestOptimization(GeneticAlgorithm metaLevelAlgorithm) { 169 metaLevelAlgorithm.Start(); 170 do { 171 Thread.Sleep(1000); 172 Console.Clear(); 173 try { 174 foreach (var result in metaLevelAlgorithm.Results) { 175 Console.WriteLine(result.ToString()); 176 if (result.Name == "Population") { 177 RunCollection rc = (RunCollection)result.Value; 178 var orderedRuns = rc.OrderBy(x => x.Results["BestQuality"]); 179 foreach (IRun run in orderedRuns) { 180 Console.WriteLine("Q: {0} PoSi: {1} MuRa: {2} MuOp: {3}", 181 ((DoubleValue)run.Results["BestQuality"]).Value.ToString("0.00").PadLeft(4, ' '), 182 ((IntValue)run.Parameters["PopulationSize"]).Value.ToString().PadLeft(3, ' '), 183 ((DoubleValue)run.Parameters["MutationProbability"]).Value.ToString("0.00").PadRight(3, ' '), 184 run.Parameters["Mutator"]); 185 } 186 } 238 ContentManager.Initialize(new PersistenceContentManager()); 239 string path = Path.Combine(AppDomain.CurrentDomain.BaseDirectory, "Results"); 240 if(!Directory.Exists(path)) 241 Directory.CreateDirectory(path); 242 string id = DateTime.Now.ToString("MM.dd.yy - HH;mm;ss,ffff"); 243 string resultPath = Path.Combine(path, string.Format("Test - {0} - Result.hl", id)); 244 string outputPath = Path.Combine(path, string.Format("Test - {0} - Console.txt", id)); 245 246 using (var sw = new StreamWriter(outputPath)) { 247 metaLevelAlgorithm.Start(); 248 int i = 0; 249 int currentGeneration = -1; 250 do { 251 Thread.Sleep(500); 252 try { 253 if (metaLevelAlgorithm.Results.ContainsKey("Generations") && ((IntValue)metaLevelAlgorithm.Results["Generations"].Value).Value != currentGeneration) { 254 StringBuilder sb = new StringBuilder(); 255 sb.AppendLine(DateTime.Now.ToLongTimeString()); 256 sb.AppendLine("================================="); 257 258 foreach (var result in metaLevelAlgorithm.Results) { 259 sb.AppendLine(result.ToString()); 260 if (result.Name == "Population") { 261 RunCollection rc = (RunCollection)result.Value; 262 var orderedRuns = rc.OrderBy(x => x.Results["BestQuality"]); 263 264 sb.AppendLine("Qality PoSi MutRa Eli GrSi MutOp"); 265 foreach (IRun run in orderedRuns) { 266 sb.AppendLine(string.Format("{0} {1} {2} {3} {4} {5}", 267 ((DoubleValue)run.Results["BestQuality"]).Value.ToString("#0.00").PadLeft(7, ' '), 268 ((IntValue)run.Parameters["PopulationSize"]).Value.ToString().PadLeft(3, ' ').PadRight(3, ' '), 269 ((DoubleValue)run.Parameters["MutationProbability"]).Value.ToString("0.00").PadLeft(5, ' '), 270 ((IntValue)run.Parameters["Elites"]).Value.ToString().PadLeft(3, ' '), 271 ((TournamentSelector)run.Parameters["Selector"]).GroupSizeParameter.Value.ToString().PadLeft(4, ' '), 272 run.Parameters["Mutator"])); 273 } 274 } 275 } // foreach 276 Console.Clear(); 277 Console.WriteLine(sb.ToString()); 278 sw.WriteLine(sb.ToString()); 279 sw.Flush(); 280 currentGeneration = ((IntValue)metaLevelAlgorithm.Results["Generations"].Value).Value; 281 } // if 282 if (i % 30 == 0) GC.Collect(); 283 i++; 187 284 } 188 } 189 catch { } 190 } while (metaLevelAlgorithm.ExecutionState != ExecutionState.Stopped); 191 285 catch { } 286 } while (metaLevelAlgorithm.ExecutionState != ExecutionState.Stopped); 287 } 288 289 Console.WriteLine(); 290 Console.WriteLine("Storing..."); 291 292 ContentManager.Save(metaLevelAlgorithm, resultPath, true); 192 293 Console.WriteLine("Finished"); 193 294 } -
branches/HeuristicLab.MetaOptimization/HeuristicLab.MetaOptimization.sln
r4997 r5023 56 56 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Debug|x86.ActiveCfg = Debug|x86 57 57 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Debug|x86.Build.0 = Debug|x86 58 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Release|Any CPU.ActiveCfg = Release|x86 58 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Release|Any CPU.ActiveCfg = Release|Any CPU 59 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Release|Any CPU.Build.0 = Release|Any CPU 59 60 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Release|Mixed Platforms.ActiveCfg = Release|x86 60 61 {0E232F46-FD0B-4FEA-8C22-AF18DE0D151E}.Release|Mixed Platforms.Build.0 = Release|x86 -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization.Views/3.3/HeuristicLab.Problems.MetaOptimization.Views-3.3.csproj
r4984 r5023 55 55 </Reference> 56 56 <Reference Include="HeuristicLab.Data-3.3"> 57 <HintPath>..\..\..\..\..\..\ Program Files\HeuristicLab 3.3\HeuristicLab.Data-3.3.dll</HintPath>57 <HintPath>..\..\..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Data-3.3.dll</HintPath> 58 58 </Reference> 59 59 <Reference Include="HeuristicLab.Data.Views-3.3"> -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Analyzers/BestParameterConfigurationAnalyzer.cs
r5009 r5023 17 17 [StorableClass] 18 18 public sealed class BestParameterConfigurationAnalyzer : SingleSuccessorOperator, IAnalyzer { 19 // Wagner: Spezielle View für die Lösungen (ParameterConfigurations): So wie bei Runs: die zu Optimierenden Parameter(-werte) der besten solution anzeigen20 19 21 20 public ScopeTreeLookupParameter<ParameterConfigurationTree> ParameterConfigurationParameter { … … 62 61 ResultCollection results = ResultsParameter.ActualValue; 63 62 DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue; 64 ItemArray<ParameterConfigurationTree> parameter Configurations = ParameterConfigurationParameter.ActualValue;63 ItemArray<ParameterConfigurationTree> parameterTrees = ParameterConfigurationParameter.ActualValue; 65 64 66 65 int i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index; 67 66 68 EngineAlgorithm bestAlg = ((EngineAlgorithm)((ParameterConfigurationTree)parameter Configurations[i]).ActualValue.Value);67 EngineAlgorithm bestAlg = ((EngineAlgorithm)((ParameterConfigurationTree)parameterTrees[i]).ActualValue.Value); 69 68 Run bestRun = new Run(bestAlg); 69 ((ParameterConfigurationTree)parameterTrees[i]).CollectResultValues(bestRun.Results); 70 70 71 if (bestKnownQuality == null || qualities[i].Value < bestKnownQuality.Value) { 71 if (bestKnownQuality == null || qualities[i].Value < bestKnownQuality.Value) { // todo: respect Maximization:true/false 72 72 BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[i].Value); 73 73 BestKnownSolutionParameter.ActualValue = bestRun; … … 83 83 } 84 84 85 // population 85 86 RunCollection rc = new RunCollection(); 86 87 foreach (ParameterConfigurationTree pc in parameterConfigurations.OrderBy(x => x.Quality.Value*-1)) { 88 IAlgorithm alg = (IAlgorithm)pc.ActualValue.Value; 87 foreach (ParameterConfigurationTree pt in parameterTrees.OrderByDescending(x => x.BestQuality.Value)) { // todo: respect Maximization:true/false 88 IAlgorithm alg = (IAlgorithm)pt.ActualValue.Value; 89 89 alg.StoreAlgorithmInEachRun = false; 90 90 IRun run = new Run(alg); 91 pt.CollectResultValues(run.Results); 91 92 rc.Add(run); 92 93 } … … 98 99 results["Population"].Value = rc; 99 100 } 100 GC.Collect();101 101 102 102 return base.Apply(); -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/ParameterConfigurationTree.cs
r5009 r5023 13 13 [StorableClass] 14 14 public class ParameterConfigurationTree : ValueConfiguration { 15 //[Storable] 16 //protected EngineAlgorithm algorithm; 17 //public EngineAlgorithm Algorithm { 18 // get { return algorithm; } 19 // set { 20 // if (algorithm != value) { 21 // if (algorithm != null) DeregisterAlgorithmEvents(); 22 // algorithm = value; 23 // if (algorithm != null) RegisterAlgorithmEvents(); 24 // OnAlgorithmChanged(); 25 // } 26 // } 27 //} 15 [Storable] 16 public EngineAlgorithm Algorithm { 17 get { return (EngineAlgorithm)base.ActualValue.Value; } 18 set { 19 base.ActualValue.Value = value; 20 } 21 } 28 22 29 23 [Storable] 30 private DoubleValue quality;31 public DoubleValue Quality {32 get { return quality; }24 private DoubleValue bestQuality; 25 public DoubleValue BestQuality { 26 get { return bestQuality; } 33 27 set { 34 if ( quality != value) {35 if ( quality != null) DeregisterQualityEvents();36 quality = value;37 if ( quality != null) RegisterQualityEvents();28 if (bestQuality != value) { 29 if (bestQuality != null) DeregisterQualityEvents(); 30 bestQuality = value; 31 if (bestQuality != null) RegisterQualityEvents(); 38 32 OnQualityChanged(); 39 33 } … … 41 35 } 42 36 37 [Storable] 38 private DoubleValue averageQuality; 39 public DoubleValue AverageQuality { 40 get { return averageQuality; } 41 set { averageQuality = value; } 42 } 43 44 [Storable] 45 private DoubleValue worstQuality; 46 public DoubleValue WorstQuality { 47 get { return worstQuality; } 48 set { worstQuality = value; } 49 } 50 51 [Storable] 52 private DoubleValue qualityVariance; 53 public DoubleValue QualityVariance { 54 get { return qualityVariance; } 55 set { qualityVariance = value; } 56 } 57 58 [Storable] 59 private DoubleValue qualityStandardDeviation; 60 public DoubleValue QualityStandardDeviation { 61 get { return qualityStandardDeviation; } 62 set { qualityStandardDeviation = value; } 63 } 64 65 [Storable] 66 private TimeSpanValue averageExecutionTime; 67 public TimeSpanValue AverageExecutionTime { 68 get { return averageExecutionTime; } 69 set { averageExecutionTime = value; } 70 } 71 72 [Storable] 73 private IntValue repetitions; 74 public IntValue Repetitions { 75 get { return repetitions; } 76 set { repetitions = value; } 77 } 78 79 [Storable] 80 public RunCollection Runs { get; set; } 81 43 82 #region constructors and cloning 44 83 public ParameterConfigurationTree(EngineAlgorithm algorithm) : base(algorithm, algorithm.GetType()) { 45 84 this.Optimize = true; // root must always be optimized 46 this.Quality = new DoubleValue(); 47 //this.algorithm = algorithm; 85 this.BestQuality = new DoubleValue(); 48 86 } 49 87 public ParameterConfigurationTree() { … … 53 91 protected ParameterConfigurationTree(bool deserializing) : base(deserializing) { } 54 92 protected ParameterConfigurationTree(ParameterConfigurationTree original, Cloner cloner) : base(original, cloner) { 55 this.quality = cloner.Clone(original.Quality); 93 this.bestQuality = cloner.Clone(original.BestQuality); 94 this.Algorithm.Prepare(); 95 this.Algorithm.Runs.Clear(); 56 96 Initialize(); 57 97 } … … 67 107 private void Initialize() { 68 108 //if (algorithm != null) RegisterAlgorithmEvents(); 69 if (quality != null) RegisterQualityEvents(); 109 if (bestQuality != null) RegisterQualityEvents(); 110 } 111 112 public virtual void CollectResultValues(IDictionary<string, IItem> values) { 113 values.Add("RunsAverageExecutionTime", AverageExecutionTime); 114 values.Add("Repetitions", Repetitions); 115 values.Add("RunsBestQuality", BestQuality); 116 values.Add("RunsAverageQuality", AverageQuality); 117 values.Add("RunsWorstQuality", WorstQuality); 118 values.Add("RunsQualityVariance", QualityVariance); 119 values.Add("RunsQualityStandardDeviation", QualityStandardDeviation); 120 values.Add("Runs", Runs); 70 121 } 71 122 … … 89 140 //} 90 141 private void RegisterQualityEvents() { 91 Quality.ValueChanged += new EventHandler(Quality_ValueChanged);142 BestQuality.ValueChanged += new EventHandler(Quality_ValueChanged); 92 143 } 93 144 private void DeregisterQualityEvents() { 94 Quality.ValueChanged -= new EventHandler(Quality_ValueChanged);145 BestQuality.ValueChanged -= new EventHandler(Quality_ValueChanged); 95 146 } 96 147 … … 99 150 } 100 151 #endregion 152 101 153 } 102 154 } -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/ParameterConfigurations/ParameterConfiguration.cs
r5009 r5023 127 127 this.ActualValue = cloner.Clone(original.ActualValue); 128 128 this.optimize = original.optimize; 129 this.actualValueConfigurationIndex = original.actualValueConfigurationIndex; 129 130 if (this.valueConfigurations != null) RegisterValueConfigurationEvents(); 130 131 } … … 270 271 271 272 public void Parameterize(IValueParameter parameter) { 272 parameter.ActualValue = this.ActualValue.Value; 273 if (Optimize) { 274 if (this.ActualValue.Value is IParameterizedItem) { 275 this.ValueConfigurations.CheckedItems.ElementAt(actualValueConfigurationIndex).Parameterize((IParameterizedItem)this.ActualValue.Value); 276 } 277 } 278 parameter.Value = this.ActualValue.Value; 273 279 } 274 280 … … 298 304 this.ValueConfigurations.ElementAt(i).Cross(otherPc.ValueConfigurations.ElementAt(i), random); 299 305 } 306 if (random.NextDouble() > 0.5) { 307 actualValueConfigurationIndex = ((ParameterConfiguration)other).actualValueConfigurationIndex; 308 } 300 309 this.ActualValue = this.ValueConfigurations.CheckedItems.ElementAt(actualValueConfigurationIndex).ActualValue; 301 310 } -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/RangeConstraints/DoubleValueRange.cs
r5009 r5023 21 21 } 22 22 23 p ublic override DoubleValue GetRandomValue(IRandom random) {23 protected override DoubleValue GetRandomSample(IRandom random) { 24 24 double val; 25 25 do { -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/RangeConstraints/IntValueRange.cs
r5009 r5023 21 21 } 22 22 23 p ublic override IntValue GetRandomValue(IRandom random) {23 protected override IntValue GetRandomSample(IRandom random) { 24 24 int val; 25 25 do { -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/RangeConstraints/PercentValueRange.cs
r5009 r5023 21 21 } 22 22 23 p ublic override PercentValue GetRandomValue(IRandom random) {23 protected override PercentValue GetRandomSample(IRandom random) { 24 24 double val; 25 25 do { -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/RangeConstraints/Range.cs
r5009 r5023 191 191 #endregion 192 192 193 public abstract T GetRandomValue(IRandom random); 193 public T GetRandomValue(IRandom random) { 194 // by a chance return the extreme values of this range to intensify search in those regions 195 if (random.NextDouble() < 0.1) { 196 if (random.NextDouble() < 0.5) { 197 return LowerBound; 198 } else { 199 return UpperBound; 200 } 201 } 202 203 // otherwise sample a random value from the range 204 return GetRandomSample(random); 205 } 206 207 protected abstract T GetRandomSample(IRandom random); 194 208 195 209 IItem IRange.GetRandomValue(IRandom random) { -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Encodings/ValueConfigurations/ValueConfiguration.cs
r5009 r5023 6 6 using HeuristicLab.Data; 7 7 using System.Drawing; 8 using HeuristicLab.Encodings.RealVectorEncoding; 9 using HeuristicLab.Encodings.IntegerVectorEncoding; 8 10 9 11 namespace HeuristicLab.Problems.MetaOptimization { … … 92 94 [StorableConstructor] 93 95 protected ValueConfiguration(bool deserializing) { } 94 protected ValueConfiguration(ValueConfiguration original, Cloner cloner) : base(original, cloner) { 96 protected ValueConfiguration(ValueConfiguration original, Cloner cloner) 97 : base(original, cloner) { 95 98 this.ParameterConfigurations = cloner.Clone(original.parameterConfigurations); 96 99 this.actualValue = cloner.Clone(original.ActualValue); … … 228 231 if (rangeConstraint != null) { 229 232 if (this.actualValue.ValueDataType == typeof(IntValue)) { 230 this.actualValue.Value = new IntValue((((IntValue)this.actualValue.Value).Value + ((IntValue)other.ActualValue.Value).Value) / 2); 233 //this.actualValue.Value = new IntValue((((IntValue)this.actualValue.Value).Value + ((IntValue)other.ActualValue.Value).Value) / 2); 234 235 IntegerVector[] parents = new IntegerVector[2]; 236 parents[0] = new IntegerVector(new int[] { ((IntValue)this.actualValue.Value).Value }); 237 parents[1] = new IntegerVector(new int[] { ((IntValue)other.ActualValue.Value).Value }); 238 239 this.actualValue.Value = new IntValue(HeuristicLab.Encodings.IntegerVectorEncoding.DiscreteCrossover.Apply(random, parents[0], parents[1]).First()); 240 231 241 } else if (this.actualValue.ValueDataType == typeof(DoubleValue)) { 232 this.actualValue.Value = new DoubleValue((((DoubleValue)this.actualValue.Value).Value + ((DoubleValue)other.ActualValue.Value).Value) / 2); 242 //this.actualValue.Value = new DoubleValue((((DoubleValue)this.actualValue.Value).Value + ((DoubleValue)other.ActualValue.Value).Value) / 2); 243 RealVector[] parents = new RealVector[2]; 244 parents[0] = new RealVector( new double[] {((DoubleValue)this.actualValue.Value).Value} ); 245 parents[1] = new RealVector( new double[] {((DoubleValue)other.ActualValue.Value).Value} ); 246 247 if (random.NextDouble() < 0.5) { 248 this.actualValue.Value = new DoubleValue(AverageCrossover.Apply(random, new ItemArray<RealVector>(parents)).First()); 249 } else { 250 this.actualValue.Value = new DoubleValue(HeuristicLab.Encodings.RealVectorEncoding.DiscreteCrossover.Apply(random, new ItemArray<RealVector>(parents)).First()); 251 } 252 //this.actualValue.Value = new DoubleValue(AverageCrossover.Apply(random, new ItemArray<RealVector>(parents)).First()); 253 233 254 } else if (this.actualValue.ValueDataType == typeof(PercentValue)) { 234 this.actualValue.Value = new PercentValue((((PercentValue)this.actualValue.Value).Value + ((PercentValue)other.ActualValue.Value).Value) / 2); 255 //this.actualValue.Value = new PercentValue((((PercentValue)this.actualValue.Value).Value + ((PercentValue)other.ActualValue.Value).Value) / 2); 256 257 RealVector[] parents = new RealVector[2]; 258 parents[0] = new RealVector(new double[] { ((PercentValue)this.actualValue.Value).Value }); 259 parents[1] = new RealVector(new double[] { ((PercentValue)other.ActualValue.Value).Value }); 260 261 if (random.NextDouble() < 0.5) { 262 this.actualValue.Value = new PercentValue(AverageCrossover.Apply(random, new ItemArray<RealVector>(parents)).First()); 263 } else { 264 this.actualValue.Value = new PercentValue(HeuristicLab.Encodings.RealVectorEncoding.DiscreteCrossover.Apply(random, new ItemArray<RealVector>(parents)).First()); 265 } 266 235 267 } else if (this.actualValue.ValueDataType == typeof(BoolValue)) { 236 bool first = ((BoolValue)this.actualValue.Value).Value; 237 bool second = ((BoolValue)other.ActualValue.Value).Value; 238 if (first && second) { 239 this.actualValue.Value = new BoolValue(true); 240 } else if (!first && !second) { 241 this.actualValue.Value = new BoolValue(false); 242 } else { 243 if (random.NextDouble() > 0.5) 244 this.actualValue.Value = new BoolValue(true); 245 else 246 this.actualValue.Value = new BoolValue(false); 247 } 268 if (random.NextDouble() > 0.5) 269 this.actualValue.Value = this.actualValue.Value; 270 else 271 this.actualValue.Value = other.ActualValue.Value; 248 272 } else { 249 273 throw new NotImplementedException(); -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Evaluators/MetaOptimizationEvaluator.cs
r5009 r5023 1 1 using System; 2 using System.Linq; 2 3 using System.Threading; 3 4 using HeuristicLab.Common; … … 8 9 using HeuristicLab.Parameters; 9 10 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; 11 using System.Collections.Generic; 10 12 11 13 namespace HeuristicLab.Problems.MetaOptimization { … … 69 71 algorithm.Stopped += new EventHandler(ActualValue_Stopped); 70 72 71 double qualitySum = 0; 73 List<double> qualities = new List<double>(); 74 List<TimeSpan> executionTimes = new List<TimeSpan>(); 75 algorithm.Prepare(true); 72 76 73 //foreach (ISingleObjectiveProblem problem in ProblemsParameter.ActualValue) { 74 algorithm.Engine = new SequentialEngine.SequentialEngine(); 75 //algorithm.Problem = problem; 76 algorithm.Prepare(); 77 algorithm.Start(); 78 while (!algorithmStopped) { 79 Thread.Sleep(1000); // wait for algorithm to complete; do not rely on Algorithm.ExecutionState here, because change of ExecutionState happens before Run is added (which causes problems because Algorithm might get cloned when its started already) 77 for (int i = 0; i < Repetitions.Value; i++) { 78 algorithm.Engine = new SequentialEngine.SequentialEngine(); 79 algorithm.Prepare(); 80 algorithm.Start(); 81 while (!algorithmStopped) { 82 Thread.Sleep(200); // wait for algorithm to complete; do not rely on Algorithm.ExecutionState here, because change of ExecutionState happens before Run is added (which causes problems because Algorithm might get cloned when its started already) 83 } 84 qualities.Add(((DoubleValue)algorithm.Results["BestQuality"].Value).Value); 85 executionTimes.Add(algorithm.ExecutionTime); 86 87 algorithmStopped = false; 80 88 } 81 double quality = ((DoubleValue)algorithm.Results["BestQuality"].Value).Value;82 ParameterConfigurationParameter.ActualValue.Quality.Value = quality;83 qualitySum += quality;84 //}85 86 89 algorithm.Stopped -= new EventHandler(ActualValue_Stopped); 87 90 88 //double qualityAvg = qualitySum / ProblemsParameter.ActualValue.Count; 89 //this.QualityParameter.ActualValue = new DoubleValue(qualityAvg); 91 qualities = qualities.OrderBy(x => x).ToList(); // todo: respect Maximization:true/false 92 93 ParameterConfigurationParameter.ActualValue.AverageExecutionTime = new TimeSpanValue(TimeSpan.FromMilliseconds(executionTimes.Average(t => t.TotalMilliseconds))); 94 ParameterConfigurationParameter.ActualValue.Repetitions = Repetitions; 95 ParameterConfigurationParameter.ActualValue.BestQuality = new DoubleValue(qualities.First()); 96 ParameterConfigurationParameter.ActualValue.AverageQuality = new DoubleValue(qualities.Average()); 97 ParameterConfigurationParameter.ActualValue.WorstQuality = new DoubleValue(qualities.Last()); 98 ParameterConfigurationParameter.ActualValue.QualityVariance = new DoubleValue(qualities.Variance()); 99 ParameterConfigurationParameter.ActualValue.QualityStandardDeviation = new DoubleValue(qualities.StandardDeviation()); 100 ParameterConfigurationParameter.ActualValue.Runs = algorithm.Runs; 101 102 double quality = ParameterConfigurationParameter.ActualValue.AverageQuality.Value; // todo: also include other measures (executiontime, variance) 90 103 this.QualityParameter.ActualValue = new DoubleValue(quality); 104 105 return base.Apply(); 106 } 91 107 92 return base.Apply(); 108 public static double Variance(IEnumerable<double> source) { 109 double avg = source.Average(); 110 double d = source.Aggregate(0.0, (total, next) => total += Math.Pow(next - avg, 2)); 111 return d / (source.Count() - 1); 112 } 113 114 public static double StandardDeviation(IEnumerable<double> source) { 115 return Math.Sqrt(source.Variance()); 93 116 } 94 117 … … 96 119 algorithmStopped = true; 97 120 } 98 99 //private void ParameterizeAlgorithm() {100 // foreach (IParameterConfiguration parameter in ParameterVectorParameter.ActualValue) {101 // if (typeof(IAlgorithm).IsAssignableFrom(parameter.OperatorType)) {102 // this.AlgorithmParameter.ActualValue.Parameters[parameter.Parameter.Name].ActualValue = parameter.Parameter.ActualValue;103 // } else if (typeof(IProblem).IsAssignableFrom(parameter.OperatorType)) {104 // this.AlgorithmParameter.ActualValue.Problem.Parameters[parameter.Parameter.Name].ActualValue = parameter.Parameter.ActualValue;105 // }106 // }107 //}108 121 } 109 122 } -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/HeuristicLab.Problems.MetaOptimization-3.3.csproj
r5009 r5023 91 91 <ItemGroup> 92 92 <Compile Include="Analyzers\BestParameterConfigurationAnalyzer.cs" /> 93 <None Include="ClassDiagram1.cd" /> 93 94 <None Include="Properties\AssemblyInfo.cs.frame" /> 94 95 <None Include="HeuristicLabProblemsMetaOptimizationPlugin.cs.frame" /> -
branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Interfaces/IOptimizable.cs
r5009 r5023 15 15 void Mutate(IRandom random); 16 16 void Cross(IOptimizable other, IRandom random); 17 17 18 18 event EventHandler IsOptimizableChanged; 19 19 event EventHandler OptimizeChanged;
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